Merge branch 'main' into feat/knowledge-dark-mode
commit
49674507c6
@ -1,2 +1,3 @@
|
||||
- deepseek-chat
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||||
- deepseek-coder
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||||
- deepseek-reasoner
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||||
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@ -0,0 +1,21 @@
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model: deepseek-reasoner
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||||
label:
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||||
zh_Hans: deepseek-reasoner
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||||
en_US: deepseek-reasoner
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||||
model_type: llm
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||||
features:
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||||
- agent-thought
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||||
model_properties:
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mode: chat
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||||
context_size: 64000
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||||
parameter_rules:
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||||
- name: max_tokens
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||||
use_template: max_tokens
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||||
min: 1
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||||
max: 8192
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||||
default: 4096
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||||
pricing:
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||||
input: "4"
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||||
output: "16"
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||||
unit: "0.000001"
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||||
currency: RMB
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||||
@ -0,0 +1,39 @@
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model: gemini-2.0-flash-thinking-exp-01-21
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label:
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en_US: Gemini 2.0 Flash Thinking Exp 01-21
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model_type: llm
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features:
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- agent-thought
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- vision
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- document
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||||
- video
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- audio
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model_properties:
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mode: chat
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context_size: 32767
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parameter_rules:
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- name: temperature
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use_template: temperature
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||||
- name: top_p
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use_template: top_p
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||||
- name: top_k
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label:
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zh_Hans: 取样数量
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||||
en_US: Top k
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||||
type: int
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help:
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zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
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||||
en_US: Only sample from the top K options for each subsequent token.
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required: false
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||||
- name: max_output_tokens
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||||
use_template: max_tokens
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||||
default: 8192
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min: 1
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max: 8192
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||||
- name: json_schema
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||||
use_template: json_schema
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pricing:
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||||
input: '0.00'
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||||
output: '0.00'
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||||
unit: '0.000001'
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currency: USD
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@ -0,0 +1,469 @@
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import json
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import logging
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import os
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import uuid
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from datetime import datetime, timedelta
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from typing import Optional, cast
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||||
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from opik import Opik, Trace
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||||
from opik.id_helpers import uuid4_to_uuid7
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from core.ops.base_trace_instance import BaseTraceInstance
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from core.ops.entities.config_entity import OpikConfig
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from core.ops.entities.trace_entity import (
|
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BaseTraceInfo,
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DatasetRetrievalTraceInfo,
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GenerateNameTraceInfo,
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||||
MessageTraceInfo,
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||||
ModerationTraceInfo,
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||||
SuggestedQuestionTraceInfo,
|
||||
ToolTraceInfo,
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||||
TraceTaskName,
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||||
WorkflowTraceInfo,
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||||
)
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||||
from extensions.ext_database import db
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||||
from models.model import EndUser, MessageFile
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from models.workflow import WorkflowNodeExecution
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||||
logger = logging.getLogger(__name__)
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||||
|
||||
|
||||
def wrap_dict(key_name, data):
|
||||
"""Make sure that the input data is a dict"""
|
||||
if not isinstance(data, dict):
|
||||
return {key_name: data}
|
||||
|
||||
return data
|
||||
|
||||
|
||||
def wrap_metadata(metadata, **kwargs):
|
||||
"""Add common metatada to all Traces and Spans"""
|
||||
metadata["created_from"] = "dify"
|
||||
|
||||
metadata.update(kwargs)
|
||||
|
||||
return metadata
|
||||
|
||||
|
||||
def prepare_opik_uuid(user_datetime: Optional[datetime], user_uuid: Optional[str]):
|
||||
"""Opik needs UUIDv7 while Dify uses UUIDv4 for identifier of most
|
||||
messages and objects. The type-hints of BaseTraceInfo indicates that
|
||||
objects start_time and message_id could be null which means we cannot map
|
||||
it to a UUIDv7. Given that we have no way to identify that object
|
||||
uniquely, generate a new random one UUIDv7 in that case.
|
||||
"""
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||||
|
||||
if user_datetime is None:
|
||||
user_datetime = datetime.now()
|
||||
|
||||
if user_uuid is None:
|
||||
user_uuid = str(uuid.uuid4())
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||||
|
||||
return uuid4_to_uuid7(user_datetime, user_uuid)
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||||
|
||||
|
||||
class OpikDataTrace(BaseTraceInstance):
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||||
def __init__(
|
||||
self,
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||||
opik_config: OpikConfig,
|
||||
):
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||||
super().__init__(opik_config)
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||||
self.opik_client = Opik(
|
||||
project_name=opik_config.project,
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||||
workspace=opik_config.workspace,
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||||
host=opik_config.url,
|
||||
api_key=opik_config.api_key,
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||||
)
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||||
self.project = opik_config.project
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||||
self.file_base_url = os.getenv("FILES_URL", "http://127.0.0.1:5001")
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||||
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||||
def trace(self, trace_info: BaseTraceInfo):
|
||||
if isinstance(trace_info, WorkflowTraceInfo):
|
||||
self.workflow_trace(trace_info)
|
||||
if isinstance(trace_info, MessageTraceInfo):
|
||||
self.message_trace(trace_info)
|
||||
if isinstance(trace_info, ModerationTraceInfo):
|
||||
self.moderation_trace(trace_info)
|
||||
if isinstance(trace_info, SuggestedQuestionTraceInfo):
|
||||
self.suggested_question_trace(trace_info)
|
||||
if isinstance(trace_info, DatasetRetrievalTraceInfo):
|
||||
self.dataset_retrieval_trace(trace_info)
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||||
if isinstance(trace_info, ToolTraceInfo):
|
||||
self.tool_trace(trace_info)
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||||
if isinstance(trace_info, GenerateNameTraceInfo):
|
||||
self.generate_name_trace(trace_info)
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||||
|
||||
def workflow_trace(self, trace_info: WorkflowTraceInfo):
|
||||
dify_trace_id = trace_info.workflow_run_id
|
||||
opik_trace_id = prepare_opik_uuid(trace_info.start_time, dify_trace_id)
|
||||
workflow_metadata = wrap_metadata(
|
||||
trace_info.metadata, message_id=trace_info.message_id, workflow_app_log_id=trace_info.workflow_app_log_id
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||||
)
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||||
root_span_id = None
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||||
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||||
if trace_info.message_id:
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||||
dify_trace_id = trace_info.message_id
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||||
opik_trace_id = prepare_opik_uuid(trace_info.start_time, dify_trace_id)
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||||
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||||
trace_data = {
|
||||
"id": opik_trace_id,
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||||
"name": TraceTaskName.MESSAGE_TRACE.value,
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||||
"start_time": trace_info.start_time,
|
||||
"end_time": trace_info.end_time,
|
||||
"metadata": workflow_metadata,
|
||||
"input": wrap_dict("input", trace_info.workflow_run_inputs),
|
||||
"output": wrap_dict("output", trace_info.workflow_run_outputs),
|
||||
"tags": ["message", "workflow"],
|
||||
"project_name": self.project,
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||||
}
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self.add_trace(trace_data)
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||||
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||||
root_span_id = prepare_opik_uuid(trace_info.start_time, trace_info.workflow_run_id)
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span_data = {
|
||||
"id": root_span_id,
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||||
"parent_span_id": None,
|
||||
"trace_id": opik_trace_id,
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||||
"name": TraceTaskName.WORKFLOW_TRACE.value,
|
||||
"input": wrap_dict("input", trace_info.workflow_run_inputs),
|
||||
"output": wrap_dict("output", trace_info.workflow_run_outputs),
|
||||
"start_time": trace_info.start_time,
|
||||
"end_time": trace_info.end_time,
|
||||
"metadata": workflow_metadata,
|
||||
"tags": ["workflow"],
|
||||
"project_name": self.project,
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||||
}
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||||
self.add_span(span_data)
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||||
else:
|
||||
trace_data = {
|
||||
"id": opik_trace_id,
|
||||
"name": TraceTaskName.MESSAGE_TRACE.value,
|
||||
"start_time": trace_info.start_time,
|
||||
"end_time": trace_info.end_time,
|
||||
"metadata": workflow_metadata,
|
||||
"input": wrap_dict("input", trace_info.workflow_run_inputs),
|
||||
"output": wrap_dict("output", trace_info.workflow_run_outputs),
|
||||
"tags": ["workflow"],
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||||
"project_name": self.project,
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||||
}
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||||
self.add_trace(trace_data)
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||||
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||||
# through workflow_run_id get all_nodes_execution
|
||||
workflow_nodes_execution_id_records = (
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||||
db.session.query(WorkflowNodeExecution.id)
|
||||
.filter(WorkflowNodeExecution.workflow_run_id == trace_info.workflow_run_id)
|
||||
.all()
|
||||
)
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||||
|
||||
for node_execution_id_record in workflow_nodes_execution_id_records:
|
||||
node_execution = (
|
||||
db.session.query(
|
||||
WorkflowNodeExecution.id,
|
||||
WorkflowNodeExecution.tenant_id,
|
||||
WorkflowNodeExecution.app_id,
|
||||
WorkflowNodeExecution.title,
|
||||
WorkflowNodeExecution.node_type,
|
||||
WorkflowNodeExecution.status,
|
||||
WorkflowNodeExecution.inputs,
|
||||
WorkflowNodeExecution.outputs,
|
||||
WorkflowNodeExecution.created_at,
|
||||
WorkflowNodeExecution.elapsed_time,
|
||||
WorkflowNodeExecution.process_data,
|
||||
WorkflowNodeExecution.execution_metadata,
|
||||
)
|
||||
.filter(WorkflowNodeExecution.id == node_execution_id_record.id)
|
||||
.first()
|
||||
)
|
||||
|
||||
if not node_execution:
|
||||
continue
|
||||
|
||||
node_execution_id = node_execution.id
|
||||
tenant_id = node_execution.tenant_id
|
||||
app_id = node_execution.app_id
|
||||
node_name = node_execution.title
|
||||
node_type = node_execution.node_type
|
||||
status = node_execution.status
|
||||
if node_type == "llm":
|
||||
inputs = (
|
||||
json.loads(node_execution.process_data).get("prompts", {}) if node_execution.process_data else {}
|
||||
)
|
||||
else:
|
||||
inputs = json.loads(node_execution.inputs) if node_execution.inputs else {}
|
||||
outputs = json.loads(node_execution.outputs) if node_execution.outputs else {}
|
||||
created_at = node_execution.created_at or datetime.now()
|
||||
elapsed_time = node_execution.elapsed_time
|
||||
finished_at = created_at + timedelta(seconds=elapsed_time)
|
||||
|
||||
execution_metadata = (
|
||||
json.loads(node_execution.execution_metadata) if node_execution.execution_metadata else {}
|
||||
)
|
||||
metadata = execution_metadata.copy()
|
||||
metadata.update(
|
||||
{
|
||||
"workflow_run_id": trace_info.workflow_run_id,
|
||||
"node_execution_id": node_execution_id,
|
||||
"tenant_id": tenant_id,
|
||||
"app_id": app_id,
|
||||
"app_name": node_name,
|
||||
"node_type": node_type,
|
||||
"status": status,
|
||||
}
|
||||
)
|
||||
|
||||
process_data = json.loads(node_execution.process_data) if node_execution.process_data else {}
|
||||
|
||||
provider = None
|
||||
model = None
|
||||
total_tokens = 0
|
||||
completion_tokens = 0
|
||||
prompt_tokens = 0
|
||||
|
||||
if process_data and process_data.get("model_mode") == "chat":
|
||||
run_type = "llm"
|
||||
provider = process_data.get("model_provider", None)
|
||||
model = process_data.get("model_name", "")
|
||||
metadata.update(
|
||||
{
|
||||
"ls_provider": provider,
|
||||
"ls_model_name": model,
|
||||
}
|
||||
)
|
||||
|
||||
try:
|
||||
if outputs.get("usage"):
|
||||
total_tokens = outputs["usage"].get("total_tokens", 0)
|
||||
prompt_tokens = outputs["usage"].get("prompt_tokens", 0)
|
||||
completion_tokens = outputs["usage"].get("completion_tokens", 0)
|
||||
except Exception:
|
||||
logger.error("Failed to extract usage", exc_info=True)
|
||||
|
||||
else:
|
||||
run_type = "tool"
|
||||
|
||||
parent_span_id = trace_info.workflow_app_log_id or trace_info.workflow_run_id
|
||||
|
||||
if not total_tokens:
|
||||
total_tokens = execution_metadata.get("total_tokens", 0)
|
||||
|
||||
span_data = {
|
||||
"trace_id": opik_trace_id,
|
||||
"id": prepare_opik_uuid(created_at, node_execution_id),
|
||||
"parent_span_id": prepare_opik_uuid(trace_info.start_time, parent_span_id),
|
||||
"name": node_type,
|
||||
"type": run_type,
|
||||
"start_time": created_at,
|
||||
"end_time": finished_at,
|
||||
"metadata": wrap_metadata(metadata),
|
||||
"input": wrap_dict("input", inputs),
|
||||
"output": wrap_dict("output", outputs),
|
||||
"tags": ["node_execution"],
|
||||
"project_name": self.project,
|
||||
"usage": {
|
||||
"total_tokens": total_tokens,
|
||||
"completion_tokens": completion_tokens,
|
||||
"prompt_tokens": prompt_tokens,
|
||||
},
|
||||
"model": model,
|
||||
"provider": provider,
|
||||
}
|
||||
|
||||
self.add_span(span_data)
|
||||
|
||||
def message_trace(self, trace_info: MessageTraceInfo):
|
||||
# get message file data
|
||||
file_list = cast(list[str], trace_info.file_list) or []
|
||||
message_file_data: Optional[MessageFile] = trace_info.message_file_data
|
||||
|
||||
if message_file_data is not None:
|
||||
file_url = f"{self.file_base_url}/{message_file_data.url}" if message_file_data else ""
|
||||
file_list.append(file_url)
|
||||
|
||||
message_data = trace_info.message_data
|
||||
if message_data is None:
|
||||
return
|
||||
|
||||
metadata = trace_info.metadata
|
||||
message_id = trace_info.message_id
|
||||
|
||||
user_id = message_data.from_account_id
|
||||
metadata["user_id"] = user_id
|
||||
metadata["file_list"] = file_list
|
||||
|
||||
if message_data.from_end_user_id:
|
||||
end_user_data: Optional[EndUser] = (
|
||||
db.session.query(EndUser).filter(EndUser.id == message_data.from_end_user_id).first()
|
||||
)
|
||||
if end_user_data is not None:
|
||||
end_user_id = end_user_data.session_id
|
||||
metadata["end_user_id"] = end_user_id
|
||||
|
||||
trace_data = {
|
||||
"id": prepare_opik_uuid(trace_info.start_time, message_id),
|
||||
"name": TraceTaskName.MESSAGE_TRACE.value,
|
||||
"start_time": trace_info.start_time,
|
||||
"end_time": trace_info.end_time,
|
||||
"metadata": wrap_metadata(metadata),
|
||||
"input": trace_info.inputs,
|
||||
"output": message_data.answer,
|
||||
"tags": ["message", str(trace_info.conversation_mode)],
|
||||
"project_name": self.project,
|
||||
}
|
||||
trace = self.add_trace(trace_data)
|
||||
|
||||
span_data = {
|
||||
"trace_id": trace.id,
|
||||
"name": "llm",
|
||||
"type": "llm",
|
||||
"start_time": trace_info.start_time,
|
||||
"end_time": trace_info.end_time,
|
||||
"metadata": wrap_metadata(metadata),
|
||||
"input": {"input": trace_info.inputs},
|
||||
"output": {"output": message_data.answer},
|
||||
"tags": ["llm", str(trace_info.conversation_mode)],
|
||||
"usage": {
|
||||
"completion_tokens": trace_info.answer_tokens,
|
||||
"prompt_tokens": trace_info.message_tokens,
|
||||
"total_tokens": trace_info.total_tokens,
|
||||
},
|
||||
"project_name": self.project,
|
||||
}
|
||||
self.add_span(span_data)
|
||||
|
||||
def moderation_trace(self, trace_info: ModerationTraceInfo):
|
||||
if trace_info.message_data is None:
|
||||
return
|
||||
|
||||
start_time = trace_info.start_time or trace_info.message_data.created_at
|
||||
|
||||
span_data = {
|
||||
"trace_id": prepare_opik_uuid(start_time, trace_info.message_id),
|
||||
"name": TraceTaskName.MODERATION_TRACE.value,
|
||||
"type": "tool",
|
||||
"start_time": start_time,
|
||||
"end_time": trace_info.end_time or trace_info.message_data.updated_at,
|
||||
"metadata": wrap_metadata(trace_info.metadata),
|
||||
"input": wrap_dict("input", trace_info.inputs),
|
||||
"output": {
|
||||
"action": trace_info.action,
|
||||
"flagged": trace_info.flagged,
|
||||
"preset_response": trace_info.preset_response,
|
||||
"inputs": trace_info.inputs,
|
||||
},
|
||||
"tags": ["moderation"],
|
||||
}
|
||||
|
||||
self.add_span(span_data)
|
||||
|
||||
def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo):
|
||||
message_data = trace_info.message_data
|
||||
if message_data is None:
|
||||
return
|
||||
|
||||
start_time = trace_info.start_time or message_data.created_at
|
||||
|
||||
span_data = {
|
||||
"trace_id": prepare_opik_uuid(start_time, trace_info.message_id),
|
||||
"name": TraceTaskName.SUGGESTED_QUESTION_TRACE.value,
|
||||
"type": "tool",
|
||||
"start_time": start_time,
|
||||
"end_time": trace_info.end_time or message_data.updated_at,
|
||||
"metadata": wrap_metadata(trace_info.metadata),
|
||||
"input": wrap_dict("input", trace_info.inputs),
|
||||
"output": wrap_dict("output", trace_info.suggested_question),
|
||||
"tags": ["suggested_question"],
|
||||
}
|
||||
|
||||
self.add_span(span_data)
|
||||
|
||||
def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo):
|
||||
if trace_info.message_data is None:
|
||||
return
|
||||
|
||||
start_time = trace_info.start_time or trace_info.message_data.created_at
|
||||
|
||||
span_data = {
|
||||
"trace_id": prepare_opik_uuid(start_time, trace_info.message_id),
|
||||
"name": TraceTaskName.DATASET_RETRIEVAL_TRACE.value,
|
||||
"type": "tool",
|
||||
"start_time": start_time,
|
||||
"end_time": trace_info.end_time or trace_info.message_data.updated_at,
|
||||
"metadata": wrap_metadata(trace_info.metadata),
|
||||
"input": wrap_dict("input", trace_info.inputs),
|
||||
"output": {"documents": trace_info.documents},
|
||||
"tags": ["dataset_retrieval"],
|
||||
}
|
||||
|
||||
self.add_span(span_data)
|
||||
|
||||
def tool_trace(self, trace_info: ToolTraceInfo):
|
||||
span_data = {
|
||||
"trace_id": prepare_opik_uuid(trace_info.start_time, trace_info.message_id),
|
||||
"name": trace_info.tool_name,
|
||||
"type": "tool",
|
||||
"start_time": trace_info.start_time,
|
||||
"end_time": trace_info.end_time,
|
||||
"metadata": wrap_metadata(trace_info.metadata),
|
||||
"input": wrap_dict("input", trace_info.tool_inputs),
|
||||
"output": wrap_dict("output", trace_info.tool_outputs),
|
||||
"tags": ["tool", trace_info.tool_name],
|
||||
}
|
||||
|
||||
self.add_span(span_data)
|
||||
|
||||
def generate_name_trace(self, trace_info: GenerateNameTraceInfo):
|
||||
trace_data = {
|
||||
"id": prepare_opik_uuid(trace_info.start_time, trace_info.message_id),
|
||||
"name": TraceTaskName.GENERATE_NAME_TRACE.value,
|
||||
"start_time": trace_info.start_time,
|
||||
"end_time": trace_info.end_time,
|
||||
"metadata": wrap_metadata(trace_info.metadata),
|
||||
"input": trace_info.inputs,
|
||||
"output": trace_info.outputs,
|
||||
"tags": ["generate_name"],
|
||||
"project_name": self.project,
|
||||
}
|
||||
|
||||
trace = self.add_trace(trace_data)
|
||||
|
||||
span_data = {
|
||||
"trace_id": trace.id,
|
||||
"name": TraceTaskName.GENERATE_NAME_TRACE.value,
|
||||
"start_time": trace_info.start_time,
|
||||
"end_time": trace_info.end_time,
|
||||
"metadata": wrap_metadata(trace_info.metadata),
|
||||
"input": wrap_dict("input", trace_info.inputs),
|
||||
"output": wrap_dict("output", trace_info.outputs),
|
||||
"tags": ["generate_name"],
|
||||
}
|
||||
|
||||
self.add_span(span_data)
|
||||
|
||||
def add_trace(self, opik_trace_data: dict) -> Trace:
|
||||
try:
|
||||
trace = self.opik_client.trace(**opik_trace_data)
|
||||
logger.debug("Opik Trace created successfully")
|
||||
return trace
|
||||
except Exception as e:
|
||||
raise ValueError(f"Opik Failed to create trace: {str(e)}")
|
||||
|
||||
def add_span(self, opik_span_data: dict):
|
||||
try:
|
||||
self.opik_client.span(**opik_span_data)
|
||||
logger.debug("Opik Span created successfully")
|
||||
except Exception as e:
|
||||
raise ValueError(f"Opik Failed to create span: {str(e)}")
|
||||
|
||||
def api_check(self):
|
||||
try:
|
||||
self.opik_client.auth_check()
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.info(f"Opik API check failed: {str(e)}", exc_info=True)
|
||||
raise ValueError(f"Opik API check failed: {str(e)}")
|
||||
|
||||
def get_project_url(self):
|
||||
try:
|
||||
return self.opik_client.get_project_url(project_name=self.project)
|
||||
except Exception as e:
|
||||
logger.info(f"Opik get run url failed: {str(e)}", exc_info=True)
|
||||
raise ValueError(f"Opik get run url failed: {str(e)}")
|
||||
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Reference in New Issue